Menu


Find the EGU on

Follow us on Twitter Find us on Facebook Find us on Google+ Find us on LinkedIn Find us on YouTube

Please note that this session was withdrawn and is no longer available in the respective programme. This withdrawal might have been the result of a merge with another session.

NH5.7

Statistical methods and probability: applications to coastal engineering, ocean sciences, extreme events, damage and risk
Convener: Pietro Bernardara  | Co-Conveners: Jürgen Jensen , Robert Nicholls , Barbara Zanuttigh 

Stochastic modelling is widely spreading in coastal engineering applications, ocean sciences extreme events frequency estimation, damage and risk studies.
In particular, statistical methods and probabilistic approaches are relevant for the design of protections against sea and ocean hazards, for the stochastic modelling of sea and ocean systems, for forecasting issues and for the generation and the analysis of climate change scenarios. For example, as a consequence of global sea level rise, more frequent and more extreme high sea levels are likely and may cause a higher risk of flooding and erosion processes. The change in their probability of occurrence need to be investigated. Moreover, despite global sea level trends, strong deviations occur on the local spatial scale. Accordingly, it is indispensable to consider regional scales and the spatial correlation patterns of these phenomena.
The aim of this session is to gather together ocean and coastal scientists working on statistical models, on probabilistic analysis of sea and ocean variables, on damage and risk studies, in order to share the knowledge in this topic.
In particular the focus will be on ocean hazards such as sea states, waves, sea level, storm surges, tidal flows, coastal flooding and erosion.
Relevant statistical methods could include (but not only) time series and trend analysis, extreme value frequency analysis, random fields models and spatial analysis (e.g. geostatistical approaches), estimation of dependence between ocean hazards, or the assessment of uncertainties in oceanic models. Note that, behind the pure statistical methods applications, it is the quest to identify exposed domains, characterize their proneness, and estimate the associated risks. Furthermore, optimal solutions of adaptation not only need to be efficient but in particular sustainable with respect to environment, society, and economy. For these reasons, with increasing awareness, politicians and other stakeholders are becoming interested in the implications of this development and in adequate response actions.
Thus, the session will bring together scientists working on ocean sciences and final users interested in practical impacts on economical and social activities.